Abstract

AbstractCumulus clouds make a significant contribution to the Earth's energy balance and hydrological cycle and are a major source of uncertainty in climate projections. Reducing uncertainty by expanding our understanding of the processes that drive cumulus convection is vital to the accurate identification of future global and regional climate impacts. Here we adopt an interdisciplinary approach that integrates interrelated scales from plant physiology to atmospheric turbulence. Our explicit simulations mimic the land‐atmosphere approach implemented in current numerical weather prediction, and global climate models enable us to conclude that neglecting local plant dynamic responses leads to misrepresentations in the cloud cover and midtropospheric moisture convection of up to 21% and 56%, respectively. Our approach offers insights into the key role played by the active vegetation on atmospheric convective mixing that has recently been identified as the source of half of the variance in global warming projections (i.e., equilibrium climate sensitivity).

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